Due to an increase in health care costs and inefficiency in the health care system, health care providers and service management organizations need health care maintenance systems which receive input medical claim data, correlate the medical claim data and provide a means for quantitatively and qualitatively analyzing provider performance. Because of the complex nature of medical care service data, many clinicians and administrators are not able to efficiently utilize the data. A need exists for a computer program that transforms inpatient and out patient claim data to actionable information, which is logically understood by clinicians and administrators.
Performance is quickly becoming the standard by which health care purchasers and informed consumers select their health care providers. Those responsible for the development and maintenance of provider networks search for an objective means to measure and quantify the health care services provided to their clients. Qualitative and quantitative analysis of medical provider performance is a key element for managing and improving a health care network. Operating a successful health care network requires the ability to monitor and quantify medical care costs and care quality. Oftentimes, success depends on the providers' ability to identify and correct problems in their health care system. A need exists, therefore, for an analytical tool for identifying real costs in a given health care management system.
To operate a more efficient health care system, health care providers need to optimize health care services and expenditures. Many providers practice outside established utilization and cost norms. Systems that detect inappropriate coding, eliminate potentially inappropriate services or conduct encounter-based payment methodology are insufficient for correcting the inconsistencies of the health care system. When a complication or comorbidity is encountered during the course of treatment, many systems do not reclassify the treatment profile. Existing systems do not adjust for casemix, concurrent conditions or recurrent conditions. A system that compensates for casemix should identify the types of illnesses treated in a given population, determine the extent of resource application to specific types of illnesses, measure and compare the treatment patterns among individual and groups of health care providers and educate providers to more effectively manage risk. When profiling claims, existing systems establish classifications that do not contain a manageable number of groupings, are not clinically homogeneous or are not statistically stable. A need exists, therefore, for a patient classification system that accounts for differences in patient severity and establishes a clearly defined unit of analysis.
For many years, computer-implemented programs for increasing health care efficiency have been available for purchase. Included within the current patent literature and competitive information are many programs that are directed to the basic concept of health care systems.
The Mohlenbrock, et al., U.S. Pat. No. 4,667,292, issued in 1987, discloses a medical reimbursement computer system which generates a list identifying the most appropriate diagnostic-related group (DRG) and related categories applicable to a given patient for inpatient claims only. The list is limited by a combination of the characteristics of the patient and an initial principal diagnosis. A physician can choose a new designation from a list of related categories while the patient is still being treated. The manually determined ICD-9 numbers can be applied to an available grouper computer program to compare the working DRG to the government's DRG.
The Mohlenbrock, et al., U.S. Pat. No. 5,018,067, issued in 1991, discloses an apparatus and method for improved estimation of health resource consumption through the use of diagnostic and/or procedure grouping and severity of illness indicators. This system is a computer-implemented program that calculates the amount of payment to the health provider by extracting the same input data as that identified in the Mohlenbrock '292 patent teaching the DRG System. The system calculates the severity of the patient's illness then classifies each patient into sub-categories of resource consumption within a designated DRG. A computer combines the input data according to a formula consisting of constants and variables. The variables are known for each patient and relate to the number of ICD codes and the government weighing of the codes. The software program determines a set of constants for use in the formula for a given DRG that minimizes variances between the actual known outcomes and those estimated by use of the formula. Because it is based upon various levels of illness severity within each diagnosis, the results of this system provide a much more homogenous grouping of patients than is provided by the DRGs. Providers can be compared to identify those providers whose practice patterns are of the highest quality and most cost efficient. A set of actual costs incurred can be compared with the estimated costs. After the initial diagnosis, the system determines the expected costs of treating a patient.
The Schneiderman U.S. Pat. No. 5,099,424, issued in 1992, discloses a model user application system for clinical data processing that tracks and monitors a simulated outpatient medical practice using database management software. The system allows for a database of patients and the entry of EKG and/or chest x-ray (CXR) test results into separate EKG/CXR records as distinct logical entities. This system requires entry of test results that are not part of the medical claim itself. If not already present, the entry creates a separate lab record that may be holding blood work from the same lab test request. Portions of the information are transferred to the lab record for all request situations. Although the lab record data routine is limited to blood work, each time the routine is run, historical parameter data are sent to a companion lab record along with other data linking both record types. The system also includes a revision of the system's specialist record and the general recommendation from an earlier work for more explicit use in information management.
The Tawil U.S. Pat. No. 5,225,976, issued in 1993, discloses an automated health benefit processing system. This system minimizes health care costs by informing the purchasers of medical services about market conditions of those medical services. A database includes, for each covered medical procedure in a specific geographic area, a list of capable providers and their charges. A first processor identifies the insured then generates a treatment plan and the required medical procedures. Next, the first processor retrieves information related to the medical procedures and appends the information to the treatment plan. A second processor generates an actual treatment record including the actual charges. A third processor compares the plan and the actual records to determine the amounts payable to the insured and the provider.
The Ertel U.S. Pat. No. 5,307,262, issued in 1994, discloses a patient data quality review method and system. The system performs data quality checks and generates documents to ensure the best description of a case. The system provides file security and tracks the cases through the entire review process. Patient data and system performance data are aggregated into a common database that interfaces with existing data systems. Data profiles categorize data quality problems by type and source. Problems are classified as to potential consequences. The system stores data, processes it to determine misreporting, classifies the case and displays the case-specific patient data and aggregate patient data.
The Holloway, et al., U.S. Pat. No. 5,253,164, issued in 1993, discloses a system and method for detecting fraudulent medical claims via examination of service codes. This system interprets medical claims and associated representation according to specific rules and against a predetermined CPT-4 code database. A knowledge base interpreter applies the knowledge base using the rules specified. The database can be updated as new methods of inappropriate coding are discovered. The system recommends appropriate CPT codes or recommends pending the claims until additional information is received. The recommendations are based on the decision rules that physician reviewers have already used on a manual basis.
The Cummings U.S. Pat. No. 5,301,105, issued in 1994, discloses an all care health management system. The patient-based system includes an integrated interconnection and interaction of essential health care participants to provide patients with complete support. The system includes interactive participation with the patients employers and banks. The system also integrates all aspects of the optimization of health-inducing diet and life style factors and makes customized recommendations for health-enhancing practices. By pre-certifying patients and procedures, the system enhances health care efficiency and reduces overhead costs.
The Dorne U.S. Pat. No. 5,325,293, issued in 1994, discloses a system and method for correlating medical procedures and medical billing codes. After an examination, the system automatically determines raw codes directly associated with all of the medical procedures performed or planned to be performed with a particular patient. The system allows the physician to modify the procedures after performing the examination. By manipulating the raw codes, the system generates intermediate and billing codes without altering the raw codes.
The Kessler, et al., U.S. Pat. No. 5,324,077, issued in 1994, discloses a negotiable medical data draft for tracking and evaluating medical treatment. This system gathers medical data from ambulatory visits using a medical data draft completed by the provider to obtain payment for services, to permit quality review by medical insurers. In exchange for immediate partial payment of services, providers are required to enter data summarizing the patient's visit on negotiable medical drafts. The partial payments are incentives to providers for participating in the system.
The Torma, et al., U.S. Pat. No. 5,365,425, issued in 1994, discloses a method and system for measuring management effectiveness. Quality, cost and access are integrated to provide a holistic description of the effectiveness of care. The system compares general medical treatment databases and surveyed patient perceptions of care. Adjustments based on severity of illness, case weight and military costs are made to the data to ensure that all medical facilities are considered fairly.
Health Chex's PEER-A-MED computer program is a physician practice profiling system that provides case-mix adjusted physician analysis based on a clinical severity concept. The system employs a multivariate linear regression analysis to appropriately adjust for case-mix. After adjusting for the complexity of the physician's caseload, the system compares the relative performance of a physician to the performance of the peer group as a whole. The system also compares physician utilization performance for uncomplicated, commonly seen diagnosis. Because the full spectrum of clinical care that is rendered to a patient is not represented in its databases, the system is primarily used as an economic performance measurement tool. This system categorizes the claims into general codes including acute, chronic, mental health and pregnancy. Comorbidity and CPT-4 codes adjust for acuity level. The codes are subcategorized into twenty cluster groups based upon the level of severity. The system buckets the codes for the year and contains no apparent episode building methodology. While the PEER-A-MED system contains clinically heterogeneous groupings, the groupings are not episode-based and recurrent episodes cannot be accounted.
Ambulatory Care Groups (ACG) provides a patient-based system that uses the patient and the analysis unit. Patients are assigned to an diagnosis group and an entire year's claims are bucketed into thirty-one diagnosis groups. By pre-defining the diagnosis groups, this is a bucketing-type system and claim management by medical episode does not occur. The system determines if a claim is in one of the buckets. Because different diseases could be categorized into the same ACG, this system is not clinically homogeneous. An additional problem with ACGs is that too many diagnosis groups are in each ACG.
Ambulatory Patient Groups (APGs) are a patient classification system designed to explain the amount and type of resources used in an ambulatory visit. Patients in each APG have similar clinical characteristics and similar resource use and cost. Patient characteristics should relate to a common organ system or etiology. The resources used are constant and predictable across the patients within each APG. This system is an encounter-based system because it looks at only one of the patient's encounters with the health care system. This system mainly analyzes outpatient hospital visits and does not address inpatient services.
The GMIS system uses a bucketing procedure that profiles by clumps of diagnosis codes including 460 diagnostic episode clusters (DECs). The database is client specific and contains a flexible number and type of analytic data files. This system is episode-based, but it does not account for recurrent episodes, so a patient's complete data history within a one-year period is analyzed as one pseudo-episode. Signs and symptoms do not cluster to the actual disease state, e.g. abdominal pain and appendicitis are grouped in different clusters. This system does not use CPT-4 codes and does not shift the DEC to account for acuity changes during the treatment of a patient.
Value Health Sciences offers a value profiling system, under the trademark VALUE PROFILER, which utilizes a DB2 mainframe relational database with 1,800 groups. The system uses ICD9 and CPT-4 codes, which are bucket codes. Based on quality and cost-effectiveness of care, the system evaluates all claims data to produce case-mix-adjusted profiles of networks, specialties, providers and episodes of illness. The pseudo-episode building methodology contains clinically pre-defined time periods during which claims for a patient are associated with a particular condition and designated provider. The automated practice review system analyzes health care claims to identify and correct aberrant claims in a pre-payment mode (Value Coder) and to profile practice patterns in a post-payment mode (Value Profiler). This system does not link signs and symptoms and the diagnoses are non-comprehensive because the profiling is based on the exclusion of services. No apparent shifting of episodes occurs and the episodes can only exist for a preset time because the windows are not recurrent.
The medical claim profiling programs described in foregoing patents and non-patent literature demonstrate that, while conventional computer-implemented health care systems exist, they each suffer from the principal disadvantage of not identifying and grouping medical claims on an episodic basis or shifting episodic groupings based upon complications or co-morbidities. The present computer-implemented health care system contains important improvements and advances upon conventional health care systems by identifying concurrent and recurrent episodes, flagging records, creating new groupings, shifting groupings for changed clinical conditions, selecting the most recent claims, resetting windows, making a determination if the provider is an independent lab and continuing to collect information until an absence of treatment is detected.